In recent years there have been major advances in the prevention of cancer, including breast, colon and prostate cancer. However, to benefit from cancer chemoprevention, healthy people must adhere to the regimen despite inconvenience and some side effects. Identifying and understanding the factors that predict adherence is critical, if the long-term benefits of cancer chemopreventive therapies are to be realized. The primary objective of this application is to identify a profile of women who have had difficulty with adherence to chemoprevention for breast cancer. This profile will be characterized by demographic variables, medical history, quality of life, and health behaviors: obesity, alcohol use, cigarette smoking, and leisure-time physical activity. If women with particular characteristics are less likely to adhere to chemoprevention, then additional interventions targeting these subgroups and addressing the underlying factors that lead to the unhealthy behaviors can be designed to maximize the benefits of chemoprevention treatment. The proposed research will also examine reasons for poor adherence and the effectiveness of efforts to improve adherence. These objectives will be accomplished with a secondary analysis of a large existing clinical trial database from the Breast Cancer Prevention Trial (BCPT). The BCPT, which was funded by the National Cancer Institute (NCI) and coordinated by the National Surgical Adjuvant Breast and Bowel Project (NSABP), was designed to compare tamoxifen versus placebo for the prevention of breast cancer. The participants were 13,338 women at high risk of breast cancer. In addition to detailed drug adherence monitoring, information was collected regarding smoking history, alcohol use, exercise, and other demographic, medical and psychosocial variables. Both short term (1-month) and long term (3-year) drug adherence will be examined. The analytic approach will be based on a previously published theoretical model. Logistic regression will be performed to test the associations of drug adherence with participant characteristics that are predicted by the model. Cluster analysis will be used to identify clusters of health behaviors. Logistic regression will also be used to examine the associations between participant characteristics and reasons given for non-adherence. Logistic repeated measures modeling will be used to examine the effectiveness (in terms of causing an improvement in adherence) of efforts undertaken by clinical staff. This project will further the mission of the National Cancer Institute to support research in cancer prevention. This project will examine data from a large, completed study for the prevention of breast cancer. The results will provide information about which patients tend not to adhere to their cancer prevention medication, why patients do not always adhere, and what their medical providers can do to improve adherence.